master almanac

Computational Design and MPC Concrete Casting of Bio-receptive Photovoltaic Distinction & B-Pro Gold Prize 2017 in MArch Architectural Design MArch Architectural Design, RC7, BiotA Lab, Bartlett School of Architecture, UCL 26 Sep 2016 - 26 Sep 2017

Computational Materialization

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Group Members: Author and leader: Huang Yuan Zhao Ziwei Dourampei Eleni Maria Eskandarnia Hoda Design tutors: Marcos Cruz Christopher Leung Javier Ruiz Richard Beckett Science Advisors: Brenda Parker Paolo Bombelli Sandra Blanco

All rights reserved No part of this book may be reproduced in any form by electronic or mechanical means without permission in writing from publisher Copyright Š BiotA Lab, Research Cluster 7 Bio-receptive Photovoltaic Group Bartlett School of Architecture 22 Gordon st University College London London 2016-2017 2

B-Pro UD 2016-2017 B-Pro AD 2016-2017 Final Report Submission Final Project Almanac

of BartlettBartlett SchoolSchool of Architecture Architecture University College London University College London London, UK London, UK

Design tutors: Marcos Cruz Christopher Leung Tutor Javier Ruiz Nuria Richard AlvarezBeckett Lombardero Submitted by Huang Yuan

Submitted by Junlin Luo 1 October 2017

14 July 2017

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Our project has been established through 4 main ideas. Each one of us, through their individual thesis listed below, investigated an area of research and study of this project, producing a multi-technical and multi-material composite of MPC concrete and hydrogel.

Yuan Huang, “A comprehensive process of computational materialization based on data calculation”, 2017, Thesis.

Eleni Maria Dourampei, “The Relationship between innovative Architectural materials by integrating Algae and Electrochemical systems into bioreceptive 3 dimensional concrete structures with Algae being the current generator in the Bio-photovoltaic system (BPV), producing small quantities of energy possibly used to power micro fluidics in order to self regulate its growth”, 2017, Thesis.

Hoda Eskandarnia, “Robotic Fabrication of Bio-hybrid Material for energy generation”, 2017, Thesis.

Ziwei Zhao, ”Environmantal Consideration for the living bioconversion receptacle”, 2017, Thesis.

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Yuan Huang

Ziwei Zhao

Design and Casting Guangxi, China Tongji University, Shanghai

Environmental Studies Jiangyou, China Chongqing University, Chongqing

Eleni Maria Dourampei

Hoda Eskandarnia

Bio-photovoltaics Athens, Greece University for the Creative Arts, UK

Species and Robot Iran Mashhad University, Iran

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Introduction 1.0 Computational Design of Bio-photovoltaic Prototypes Computation Logic Differential Growth Behaviours Volumetrics Data Structure Thickness Prototypes and Analysis Geometric Growth Final Design and Analysis 2.0 Fabrication of the Hard Scaffold MPC Chemical Reaction Ingredients and Aggregates Ingredient Tests Casting Strategies Compaction in Layers Process, Result and Details 3.0 Species Research and Soft Scaffold * Algae Strain Hydrogel as Soft Scaffold 4.0 Environmental Studies and Irrigation System * Site Analysis Plants Orientation and Radiation Final Design Analysis Irrigation System 5.0 Bio-photovoltaics * Bio-photovoltaic System Assembly 6.0 Robotic Fabrication * Robotic Assembly Printing on 3D Geometry Conclusion Reference 6

* The whole project is done by the group’s coorperation although each of us has our main research area and chapters to focus on.

Chapter 1 and 2 are mainly edited by the author Yuan Huang, while chaper 3 and 6 are mainly edited by Hoda Eskandarnia, chaper 4 is mainly edited by Ziwei Zhao, chaper 5 is mainly edited

by Eleni Maria Dourampei.

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Our group’s project is mainly focusing on interactions between biophotosynthetic algae and MPC (Magnesium Phosphate) concrete, how algae could be seeded and colonies on 3 dimensional geometrical MPC concrete and how these 3 dimensional prototypes collect bio-electricity and use it to power a water misting system.

We firstly use computational techniques to design 3 dimensional geometries, such as circle differentiation, point track and we 3d print them into plastic components.

Then we cast these components with multiple strategies like multi-layer soft rubber, “sandwich� casting to prepare the negative mold for the concrete.

Later, concrete is being casted with different colors of aggregate to create our components.

Robotic printing on these prototypes will apply two kinds of materials to help bio- photovoltaic algae to be seeded on prototypes. One is hydro gel; main source of absorbing water. Second is carbon fibre; printed to be a soft scaffold to hold hydro gel and the essential material to collect bio-electricity. The relationship between hydro gel and carbon fiber will differ according to the shape of prototypes and direction of water absorption.

Electricity collection system and water pumping system is also designed on prototypes, which are placed on our site in London Zoo, according to the most shaded area, after testing the sun radiation levels.

Ultimately our prototypes will be developed to meet architectural functional requirements as well as provide suitable conditions for bio-photovoltaic algae to colonies and produce energy to support its ecosystem.

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Computational Design of Bio-photovoltaic Prototypes Computation Logic Differential Growth Behaviours Volumetrics Data Structure Thickness Prototypes and Analysis Geometric Growth Final Design and Analysis

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COMPUTATIONLOGIC There is not a specific functional node to represent Differential growth. To be specifically, growth has its superficial features such as surface inflation, general volume expansion and tendency of internal structure getting complicated. So it could be considered that calculations regarding the features mentioned above are scripts of growth. These scripts share a similarity that they have timeline for calculation; for each frame there is one time of calculation, with the data of last frame being input of the function and output the data of current frame.

Origin circle

Resample controlling points

Points iteration

Smooth points path

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GROWTHBEHAVIOURS Pscale value controls the iteration of points. In cases of points on closed circle have the same pscale value, 0.1, 0.15 and 0.2, the behavior of growth are similar and symmetrical, with bigger value of pscale, faster the growth speed becomes.

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GROWTHBEHAVIOURS When single growth circle increases to multiple growth circles, they show colonial interaction behavior, with edges expand and reach close to each other in similar behaviors. When points distance shorter to certain minimum value, edges stop expansion and has interaction with neighbor edges. Surface squeezes but never intersecting.

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GROWTHBEHAVIOURS While pscale is considered to be the function of points’ movement, there are sets of parameters to produce variation to pscale value, mainly turbulence noise in pointvop. With different noise frequency, amplitude and attenuation, pscale values to every point are different and have their own mathematical relations, producing various behaviors of differential growth. The conclusion is that initial value of pscale controls growth speed while joint effect of noise parameters controls behavior of differential growth.

Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Original Perlin Noise Frequency (-0.1, -0.1, -0.1) Offset (0, 0, 0) Amplitude = -0.252 Roughness = 0.146 Attenuation = 0.759 Turbulence = 5 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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GROWTHBEHAVIOURS Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Alligator Noise Frequency (1, 1, 1) Offset (0, 0, 0) Amplitude = 1 Roughness = 0 Attenuation = 1 Turbulence = 1 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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GROWTHBEHAVIOURS Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Alligator Noise Frequency (0, 10, 10) Offset (0, 0, 0) Amplitude = 1 Roughness = 0 Attenuation = 1 Turbulence = 10 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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GROWTHBEHAVIOURS Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Original Perlin Noise Frequency (-0.1, -0.1, -0.1) Offset (0, 0, 0) Amplitude = -0.252 Roughness = 0.146 Attenuation = 0.759 Turbulence = 5 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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GROWTHBEHAVIOURS Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Alligator Noise Frequency (1, 1, 1) Offset (0, 0, 0) Amplitude = 1 Roughness = 0 Attenuation = 1 Turbulence = 1 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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GROWTHBEHAVIOURS Pscale value = 0.15 PointVOP parameters: Turbulent Noise: signature 1D Noise Noise type: Alligator Noise Frequency (0, 10, 10) Offset (0, 0, 0) Amplitude = 1 Roughness = 0 Attenuation = 1 Turbulence = 10 Fit range: signature float Source Min = 0 Source Max = 1 Destination Min = 0.05 Destination Max = 1

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V O L U M E T R I C S Pre-frames layer up forming a volume which records the behaviour of differential growth. In order to create 3D geometries with relative more surface and self-shaded condition, another parameter is introduced to provide vertical growth, the vertical speed. While the growth happens on X-Z plane, it gradually moves upwards as well as makes results of each frame frozen and given a Y position based on their frames, thus create a volume that contains every pre-frame of the differential growth.

Resample length 0.15 Pscale value 0.2 Turbulent noise type original perlin noise Frequency (-0.1, -0.1, -0.1) Offset (0, 0, 0) Amplitude = -0.252 Roughness = 0.146 Attenuation = 0.759 Turbulence = 5 Fit destination: 0.05-1 Relax max iterations = 10 Point radius scale = 1 Smooth cutoff frequency = 0.1 Smoothing iteration = 7 Relaxing solver: Transform translate(0, 0.1, 0) Volumetric solver: merge prev-frame and input frame

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DATASTRUCTURE Differential growth has a data structure of multi-generation, this feature could also be observed in the form of outcome. Based on the rules of differential calculation above, the data could be simplified and make relative buildable adjustment.

Original Data Frame 1

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DATASTRUCTURE

Points with the same curvature

Earlier data determin later data

Unit Character 1: Mirrored protrusion

Unit Character 2: Parallel surface waving

Earlier parent data bec Dead Data (points are to each other to be cas

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coming too close sted)

Unit Character 3: Double layers

Unit Character 3: Bigger double layers

Unit Character 4: Bounches of protrusion wider parallel waving becoming Protrusion Unit Caracter 5: Protrusion expanded

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T H I C K N E S S While adding thickness to the geometry, another four parameters control the results, which are particle separation, voxel scale, influence scale and droplet scale. Each parameter returns different appearances of the surface, creating clear edges/sticky edges, pockets/holes/flat top, and thick/fragile forms. To decide values of these parameters, the capacity of casting technique need to be taken into consideration.

With deeper holes and more complicated interior structure, higher possiblity the casting would fail.

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particle separation 0.05 voxel scale 0.75 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 3 droplet scale 1

particle separation 0.15 voxel scale 0.75 influence scale 3 droplet scale 1

particle separation 0.2 voxel scale 0.75 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 0.35 influence scale 3 droplet scale1

particle separation 0.1 voxel scale 0.55 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 1.5 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 2 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 1.01 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 2.75 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 4.25 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 5 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 3 droplet scale 0.3

particle separation 0.1 voxel scale 0.75 influence scale 3 droplet scale 1

particle separation 0.1 voxel scale 0.75 influence scale 3 droplet scale 2

particle separation 0.1 voxel scale 0.75 influence scale 3 droplet scale 2.99

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P R O T O T Y P E S

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P R O T O T Y P E S

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P R O T O T Y P E S

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P R O T O T Y P E S

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P R O T O T Y P E S Components cut in three parts.Top part as water collecting components, middle part as hidden algae growth components, bottom part as leg part to hold all components above.

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P R O T O T Y P E S Components extending the folding surface width. Adjusting the thinkness from top to bottom with thinner edges at top and thicker body at bottom.

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P R O T O T Y P E S Aggregates strategy for crown-body components, dense dark aggregates for crown and porous aggregates for body.

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GEOMETRICGROWTH

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F I N A L D E S I G N Section of the final components. Thinner edges on the crown parts and thicker edges for body parts.

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SHADOWANALYSIS

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WATERANALYSIS

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Fabrication of the Hard Scaffold MPC Chemical Reaction Ingredients and Aggregates Ingredient Tests Casting Strategies Compaction in Layers Process, Result and Details

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MPCCHEMICALREACTION Megnesium-phosphate cement paste chemical reaction and materials

Hard burnt or Dead burnt Magnesium Oxide: fairly unreactive MgO

Ammonium Di-hydrogen Phosphate or Na2HPO4, KH2PO4: Acid Soluble Phosphate

Sodium Tetraborate Decahydrate Borax or Boric Acid: Set Retarder and Solvent

Magnesium Ammonium Phosphate Hexahydrate: Final Hydration Form

Na2B4O7 • 10H2O MgO + NH4H2PO4 + 5H2O ————————————— NH4MgPO4 • 6H2O NH4H2PO4 ———— NH4+ + H2PO4NH4H2PO4 ———— NH4+ + H+ + HPO42NH4H2PO4 ———— NH4+ + 2H+ + PO43MgO + H2O MgOH+ + 2H2O Mg(OH)2 2+ Mg + 6H2O

Mg(H2O)62+

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MgOH+ + OHMg(OH)2 + H3O+ Mg2+ + 2OHMg(H2O)62+

Na2B4O7 • 10H2O ————————————— NH4MgPO4 • 6H2O

Magnesium Oxide

Ammonium Di-hydrogen Phosphate

Sodium Tetraborate Decahydrate Borax

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I N G R E D I E N T S For different kinds of aggregate, the natural surface of the aggregate and sizes determine their reaction with MPC cement paste, thus for each kinds of aggregate, there need different ingredients for casting.

Theoretical surface Natural surface

Standard Ingredient: Aggregate Quantity: 1709.5g Magnesium Oxide: 207.6g Ammonium di-hydrogen phosphate: 118.6g Borax: 19.6g Water: 51.9g 1.5-time Ingredient: Aggregate Quantity: 1709.5g Magnesium Oxide: 311.4g Ammonium di-hydrogen phosphate: 177.9g Borax: 29.4g Water: 77.85g

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A G G R E G A T E S

Colored-black sand, 0.5-1.0mm

Colored-grey sand, 0.5-1.0mm

Porous aggregate, 0-0.8mm

Recycled Glass - Clear Crystal - small, 2-5mm

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INGREDIENTTESTS Through ingredient tests to different aggregates, we could conclude the most suitable ingredients for each aggregates by comparing samples porosity, water evaporation condition, weight and hardness. By observing moulds’ before and after demoulding, we could predict the reaction between components and moulds.

Aggregate Quantity: 60g Magnesium Oxide: 6g Tri-sodium phosphate: 4.2g Borax: 1g Water: 6g

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1 time fixed, with Borax 5g

1 time fixed, with Borax 4g

1 time fixed, with much more water

Aggregate Quantity: 120g Magnesium Oxide: 12g Tri-sodium phosphate: 8.4g Borax: 2g Water: 12g

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Aggregate Quantity: 120g Magnesium Oxide: 12g Tri-sodium phosphate: 8.4g Borax: 2g Water: 12g

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1 time fixed, with Borax 6g

1 time fixed, with Borax 3g

Thickness: 3cm Porous aggregate Printed hydrogel 2 days Thickness: 5cm Porous aggregate Printed hydrogel 2 days

Thickness: 5cm Non-porous aggregate Printed hydrogel 2 days

Thickness: 3cm Porous aggregate Printed hydrogel 2 days

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Rubber mould making.

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3D printing digital models and fixing with clay.

Making multiple layers of inner and outer rubber moulds.

Assembling rubber moulds and compating material in layers.

Demoulding in layers.

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Applying vaseline on rubber and 3D printing model.

Cutting and melting recycled rubber under about 190 degree centigrades.

Pouring rubber when it liquidates.

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Compacting mixture of aggregate and cement paste layer by layer

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3D printing digital models.

Making multiple layers of inner and outer rubber moulds.

Compating material in layers.

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First layer of material compaction.

Second layer of material compaction.

Third layer of material compaction.

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3D printing digital models.

Making multiple layers of inner and outer rubber moulds.

Assembling rubber moulds and compating material in layers.

Casting Process

Casting strategies for 3D geometries.

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Demoulding inner rubber moulds which are cut in pieces.

Sanding error edges produced by layering rubber moulds.

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Rubber moulds in layers.

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Process of making rubber moulds and rubber mould condition during casting. The weakness of geometry make it hard to demould and even break and the weakness of rubber vmold produce extra ridges on MPC concrete components.

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Results of crown casted alone, and crown and body casted together.

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Casting results of final components - Top Part

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Casting results of final components

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Species Research and Soft Scaffold Algae Strain Hydrogel as Soft Scaffold

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A L G A E S T R A I N Our investigation commences with isolating fast-growing species of microalgae from the local environment. The aim of this work was to find the most proper algae to inoculate with hydrogel for further experiments. The samples are collected from favourable places, for instance, shady area of tree bark, soil, artificial substrates such as wooden fences and brick walls where algae are most likely to grow . In order to examine growth rate of our species two types of nutrients namely, Tris-acetate-phosphate (TAP) medium solution and 3N-BBM+V (Bold Basal Medium with 3-Fold Nitrogen and Vitamins; Modified) were prepared. Each sample was fed in two flasks with 100 ml of 3N-BBM+V and 100 ml of TAP medium at a ratio of 1/10 . After a period of about 2 weeks, the result shows that most of the species were grew better in 3N-BBM+V compared to TAP medium . The result which conducted from this experiment lead to further exploration in this way. Therefore, the test was repeated in the same conditions, with 3N-BBM+V as an applicable nutrient for culturing collected species.

Location 1, 140 Hampstead Road

Location 2, Hampstead Road

Location 4, Arkwright Road

Location 3, Finchley Road

Location 5, Downshire Hill

Isolation of Microalgae from Local Environment.

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Species culture in 3NBBM+V Day 14

Species culture in TAP medium Day 14

Refreshing sample cultures Day 30

Refreshing sample cultures Day 60

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The Dresden University of Technology in Germany has successfully developed a method of 3D printing algae-laden hydro gel scaffolds for possible medical applications and use it with human tissue. In this project, they used micro-algae of the species Chlamydomonas Reinhardtii were embedded in 3D alginatebased hydrogel scaffolds. They used the high viscous material to build up a 3D structure in a layer-by-layer fashion. Material strands were then deposited into six-well plates in four, 20 and 50 layers constructs.

Immediately afterwards scaffolds were transferred into cacl2 solution for 10 min in order to crosslink with alginate. They tried to combine human cells and micro-algae within one scaffold in a spatially organized manner hence, to establish a patterned co culture system in which the algae are cultivated in close vicinity to human cells. This was an indication that the micro-algae have the ability to survive in the process of printing and were able to grow within the hydro gel matrix. Furthermore, the Photosynthetic activity of the embedded micro-algae was detected by changes of liquid oxygen concentration and measurement of oxygen release within the first 24 hours. This might lead to the development of new therapeutic concepts based on the delivery of oxygen or secondary metabolites as therapeutic agents by micro-algae.

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Environmental Studies and Irrigation System Site Analysis Plants Orientation and Radiation Final Design Analysis Irrigation System

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S I T E A N A L Y S I S

Land of Lions

B.U.G.S

Main pathway of visitors Boundary line

The site is located in one of the London Zoo 's graden.

It's situated beside the main path of zoo, which might have lots of tourists pass by all over the year.And oceans of different plants are growing around . One of most essential influence factor is an Pyrenean Oak tree , which is around 9 meters high and almost cover one third of the whole site.Besides, other typies of trees and bushes grow vigorously.

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In the centre of site lies a white cabin (2.1 meters high ) The main path is connecting the paradise of butterfly and lion forest, which means continuous people will pass by this area. Can u imagine that we did nothing except looking and measuring the size of the site, still attracted lots of people to stop , look and think.

From west to east, there is a altitude difference around 1.5 meters, which could bring another challenge (unstable foundation ground) Oceans of plants are growing on our site , and there are six species of them have more influence on the component than others. We list the major parameter and the position of them.

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Goat Willow (Salix caprea) 2.0m aestatisilvae Multi-branched,dense,shrubby tree Reproduct in very early spring in sheltered places.

Buxus sinica (Buxus) 0.9m everygreen small size plant Growing aboundant and prosper

Clematis Mostly vigorous, woody, climbing vines which is a deciduous and herbaceous perennial plant

Cherry laurel(Prunus Laurocerasus) 2.4m everygreen,shrub,spreading tree Fruit rounded and green at first, turning red, and then then finally blackish purple

Pyrenean Oak(Quercus Pyrenaica) 12m aestatisilvae slender more open crown than most other oaks reproduct around June and July colorful and brief display in summer Salad Burnet (Sanguisorba minor) 0.3m It is a perennial herbaceous plant typically found in dry grassy meadows, often on limestone soils. It is drought-tolerant, and grows all year around.

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O R I E N T A T I O N when the project came to more detail design, we thought that orientation, depth and width, complexity and surface area of the geometry is super essential, because all those parameter will determine the result of how much water could be remained. The less area that receive sunlight radiation, the better condition in terms of the water to remain. Therefore, we put our design prototypes in our site and analyze the radiation situation of each prototype by Grasshopper of Rhinoceros. To select the most appropriate prototype step by step. And the principle to select is mainly depends on how much sunlight will be received by the surface of each prototype, also on the difficulty level of assembly.

Total radiation: 132

Total radiation: 161

Total radiation: 124

Total radiation: 145

The results shows when put prototype on south direction, it could gain less radiation than others, because there are more shadow created by the prototype itself, the water might stay inside the component longer.

Combined with former analysis of site (solar path and wind speed and wind rose), we selected south direction as the component towards to, to minimize the sunlight radiation, and also to block wind from southeast.

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R A D I A T I O N Because there are less area that face to sunlight directly,the radiation of horizontal prototype is lower than vertical. And more surface the component has, more radiation it will receive, but there will be more shadow area at the time.So size will be more complicated at this stage

Total Radiation : 134.94

Total Radiation : 372.52

Total Radiation : 375.90

Total Radiation : 440.21

Obviously this prototype has more area exposed to sunlight and gain more radiation than horizontal groups. Another factor is weight. As chart shows, the increasing of surface and volume will not only increase the radiation area but also the difficulty to transfer the prototype. Moreover, the hydrogel could pill off from the facade easily. Therefore, we didn't choose vertical strategy to work on 123

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We set four components which came from same node and same parameter on site to figure out the how the shape affect the radiation situation. As the charts show, more surface area will bring more radiation to the component, but, also bring depth, which is important to create shadow inside,So there need a balance between complexity and depth.

I named them level 1,2,3,4 in order of time and complexity, level1 and 2 have less radiation area but could be helpless to remaining water, while level 4 have too many small pockets, which will be extreme difficult to casting the model in reality. Taking all those factors into consideration, level 3 became the final choice. It has suitable depth and surface complexity than other levels, and could be casted by ourselves.

Level 2 Total Radiation : 56.72

Level 3 Total Radiation : 60.48

Level 4 Total Radiation : 67.53

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We wanted to know the difference among those prototypes in different amount of surface area,(scale: version 1> version 2> version 3) In order to understand the particular situation, the components were put in four special dates (Equinox and Solstice), because the analysis in chapter 2 shows that site in summer might face the most disadvantageous condition than other time, so putting them in those special dates will make the comparison more specific. As the charts indicate, version 3 receive less radiation than others in summer. But in this case, the shadow area for the component is enough for the algae after last 3 steps of selection. Therefore, we prefer take version 1 as our final component to develop.

Winter (December 22)

Depth frame 3.0 Total Radiation : 0.000029

Depth frame 2.0 Total Radiation : 0.000030

Depth frame 1.0 Total Radiation : 0.000024

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Winter time Total Radiation =0.312

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Summer time Total Radiation =0.579

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IRRIGATIONSYSTEM Generally speaking, the precipitation in London could not satisfy the algae that living on the surface.(the value of expectation of daily precipitation is around 1.88 mm per day). So we put our irrigation system as an assistant. There basic working process is: use a pedestal as a collection of water, pump up the water by a pump, drop the water to the algae. The key point is the timer to control the watering automatically.

Based on the evaporation test, the duration of watering should be less than 2 days. Besides, the water could come from rain water or artificial supply.

Concret component

Hozelock Dripper Hozelock Sensor Controller automatically control the frequency of watering Water tube carry water to the place that need irrigation

Water Pump pump up the water to higher area (maximum height is 1.2meter )

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Bio-photovoltaics Bio-photovoltaic System Assembly

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BIOPHOTOVOLTAICS Bio photovoltaic devices also known as biological and electrochemical systems also called “living solar cells”, produce electrical power from light energy by relying upon the photosynthesis of living oxygenic photoautotrophic organisms such as, Moss and Algae3. Bio photovoltaic energy is a new way of converting chemical energy into electrical energy using plants that photosynthesize and preferably thrive under extreme environments. When Algae receives light, reactions split water into protons, electrons and oxygen and bio-photovoltaics use this charge separation to generate electrical energy.

Figure 01 “Moss Table” by Paolo Bombelli

http://thisisalive.com/biophotovoltaic-moss-table/

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Figure 02 “Moss FM radio” by Paolo Bombelli http://www.themethodcase.com/moss-radio-fabienne-felderpaolo-bombelli/

A bio-photovoltaic system consists of the anodic and the cathodic matrix. The anodic surface is where the electrons are generated. The anodic surface of the bio photovoltaic system needs to be a surface where the photosynthetic organism can live, grow and colonize. The anodic parts need to cover as much surface as possible and to have certain characteristics like “biocompatibility”, “water retention” and “low electric resistance”. This surface needs to be electrically conductive, like carbon fiber and needs to contain a certain amount of water; otherwise the photosynthetic organism will die or kill the protons while they are travelling from the anode to the cathode. Eso-electrogenic is the spontaneous process that drives the bio photovoltaic process. The conductive element used needs to be made out of a material with a certain degree of durability and with no much potential of oxidation. In our case, carbon fiber is the conductive material used for the anode of the BPV.

Bio-photovoltaic System Layers

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Shows the different resistances for the composite material carbon fiber (CF) + hydrogel (HG). 4gr of CF and 50gr of HG mixed and prepared, with different amount of carbon fibers. Measurements were taken over every container every 10 minutes each.

12 A

12 C

Only Hydrogel (HG)

12 B

HG + 1g of Carbon Fiber (CF)

HG + 2g of Carbon Fiber (CF)

12 D

HG + 4g of Carbon Fiber (CF)

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Robotic Fabrication Robot Assembly Printing on 3D Geometry Conclusion

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We investigate the implementation of a pneumatic extrusion system by means of air pressure and solenoid valves, that could lead to the generation of hydrogel extrusion on the various porous substratum.

A computer-controlled pneumatic extrusion system was attached to an existing motion platform’s endeffector. The platform is a Kuka KR AGILUS robotic arm; model KR 6 R900 sixx. It weighs 52kg with a 6kg payload and a maximum reach of 901mm. It has 6 axes and a +-0.03mm repeatability. At the pneumatic extrusion end-effector, algae-laden hydrogel which was contained in an aluminium vessel, extruded trough 5 to 9 mm plastic nozzles with the maximum pressure of 8.2 bars.

Final Assembly of a robotic arm system, 2017.

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PRINTON3DGEOMETRY Advances in a structural material deposition on hard scaffold enable the use of computational design for designing 3d geometry moulds with exceptional properties. This renders a viable and promising strategy for water-based manufacturing on porous surface evolving towards manufacturing BPVs. This is an investigation trough the integration of environmental analysis, material study and fabrication techniques for casting the moulds and robotically printing in order to maximise the growth area.

The 3d geometry components were designed and casted based on the computational model of a mathematically generated data with using the computational design software Houdini. Differential growth technique similar to growth logic in different render frames of growth was used as a dynamic computational process of designing. In the same way, geometric tool paths providing control and operation of the extrusion system were designed and printed based on substratum geometry to provide structural support and as a reinforcing scaffold for robotically printing of the living material. As for assembling our BPVs, filaments of carbon fibre following the geometry of the toolpath were manually embedded on the printed material. Then, the algae-laden hydrogel was continuously extruded as a second layer over it.

Air pressure

Speed Size of the nozzle Height of the nozzle

Printing parameters consideration for printing on 3d geometry

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Model 01 Air pressure: 5.5 Speed: 70 Height of the nozzle from base: 0.8 mm Number of layers: 3

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C O N C L U S I O N After analyzing the relationship between the smart materials mentioned above, and after assembling a bio-photovoltaic system with bio receptive and bio responsive elements, but also having a living organism in one of these materials surviving in it, we come up with a concept of sustainable and bio receptive Architecture that can be further applied on our every day lives.

After creating and testing several designs on bio-photovoltaic systems, it is very interesting to question, what could the energy being generated be used for. As we know, this energy produced is very limited (ca.

0.1 Wm2) and one idea is to power micro-fluidics system to support and self-regulate Algae growth by irrigating specific amount of water on specific times controlled with a switch.

Following previous studies on bio-photovoltaics developed at Cambridge University developed by Paolo Bombelli, and given that the 10,000 fold difference between bright sunlight (1000W/m2) irradiation and the current estimate for energy harvested from bio-photovoltaically electro-chemical (0.1W/m2), (Mc Cormick et al., (2011)) the possibility to power micro-fluidics to support and self-regulate algae growth, in different viscosity gels will also determine the adjustment of the carbon fibers extracting energy from Algae. Electricity collection system and water pumping system can also be designed on the prototypes.

Finally, we conclude to the point of when dealing with the concept of bio-photovoltaics, being very fragile, scientific and tactile, parameters that are surrounding it can be altered and modified to the preferred result, when the bio-photovoltaic system itself needs to always be structured in the same way. When combining this concept with Architecture, design is a parameter that can be altered and based on the needs of the components of the bio-photovoltaic but not vice versa. By designing around an element such as the BPV, gives us some specific rules that make the design more driven and directed.

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